New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Uncertainties for different classes / class imbalance problem #15
Comments
Hello, I am also working kind of similar time of the problem where we have a class imbalance problem. Sometimes, we have some classes which don't have any testing samples. Just let me know if you get any solutions. Also, did you try a custom dataset? I tried with my own dataset, but I got a bunch of 0 or -1 for AP calculation and the mean AP is also some negative values. I am not sure why. |
I am having the same problem. I trained it on FLIR dataset and I am getting nan values for my mean AP as well. Have you solved this? |
|
Hello, Thank you for the paper and the repo. I was wondering how can I deal with class imbalance during the active learning loop. Do you think the model will be choosing more samples from a class with a fewer number of images? Or will it be the other way around? Which part of the code should I tweak if I want to prioritize some of the classes during the active learning cycle? I really appreciate any help you can provide.
The text was updated successfully, but these errors were encountered: